This invention relates to methods and systems for identifying known materials or artifacts from within an unknown mixture. More particularly it can relate to system, and methods for identifying chemicals or biological constituents within a mixture of known and unknown substances; it can also relate to systems and methods for identifying shapes or patterns from a noise filled background. Still more particularly, it relates to an expert system which analyses the interaction of a first set of wavelengths of electromagnetic radiation on an unknown mixture in relation to a database of responses to that radiation of known constituents to provide concentrations of the known constituents in the mixture. Still more particularly, the expert system has two components to analyse the information received from the mixture describing the interaction of the radiation, a first subsystem utilizing a multivariate multidimensional patch algorithm trained by an evolutionary algorithm to provide the concentrations and a second subsystem utilizing a neural network also trained by an evolutionary algorithm to provide the concentration information.
Searching for the presence or absence of a known material within an unknown mixture is a classic problem with a variety of methods of solution. Most college students who took physical chemistry classes will remember the linear process-of-elimination techniques used in the laboratory to determine the unknown chemical from the sample presented to them for analysis. With the advent of the availability of increasingly powerful and inexpensive computing power, certain computer implemented processes for analyzing the problem have been brought to bear. These include various numerical analysis techniques (i.e. multivariate analysis, monte carlo techniques, etc.), genetic algorithms, and neural networks. Unfortunately, the nature of the problem presented herein is so computationally intense that solutions using these computer implemented processes are still beyond of the capability of readily available computers. What is needed is a new approach based upon but significantly more powerful than the presently known computer-implemented techniques to provide a fast and accurate solution to the problem.